Senior Member of Technical Staff, AI Research

Salesforce

Remote

Quick summary

Work type: Remote
Location: Palo Alto, CA
Salary: $148,500–$223,900 / yr
Posted: 38 days ago

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $221k

This role $186k

$135k most similar roles pay here $276k

This role pays less than 77% of similar roles. Most pay $192,006–$249,753 — the shaded band above. At the midpoint, this role pays about $186k versus about $221k for comparable roles.

Based on 240 similar postings.

Employer

About Salesforce

Salesforce is the world''s leading customer relationship management (CRM) platform, offering cloud-based software for sales, service, marketing, analytics, and application development. Industry: Enterprise Software & Cloud Computing

Salesforce currently has 86 open roles on FindRole.

Listed pay typically runs $148,500–$260,100 across 77 roles with salary data.

Most-posted roles

View all roles at Salesforce

At a glance

TL;DR · Senior Member of Technical Staff, AI Research

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Salesforce AI Research seeks a Machine Learning Engineer to join their team as an expert in developing next-generation agentic AI platforms. This role involves collaborating closely with research scientists, software engineers, product managers, and solution engineers to design, implement, and iterate on advanced AI systems for customer use. The ideal candidate will possess exceptional engineering skills, deep ML knowledge, and a track record of meaningful implementation. They should be proficient in Python, C++, or Java, have strong software engineering fundamentals, and experience with production-quality system development. Additionally, familiarity with large language models (LLMs), agentic workflows, and distributed training is essential. The candidate will work on cutting-edge AI technologies to create innovative solutions that significantly impact Salesforce customers.

Skills

Python C++ Java Docker AWS GCP Azure TensorFlow PyTorch MLflow Kubernetes CI/CD Prometheus PostgreSQL

What you'll do

Design and implement agentic AI systems using deep learning frameworks.
Collaborate with scientists to iterate on AI systems for customer solutions.
Build production-quality end-to-end AI agents and complex applications.
Deploy ML systems using Docker and cloud platforms like AWS or GCP.
Debug model training, evaluation, and inference pipelines effectively.
Optimize performance of distributed training or inference in ML systems.

What we're looking for

Exceptional engineering skills and deep ML knowledge with proven implementation.
Strong proficiency in Python, C++, Java; experience building production-quality systems.
Practical experience with LLMs and agentic workflows, including prompting and evaluation.
Hands-on experience with deep learning frameworks and model training pipelines.
Experience deploying ML systems using Docker and cloud platforms like AWS or GCP.

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